Grinding wheel system

ABSTRACT

A grinding wheel system includes a grinding wheel with at least one embedded sensor. The system also includes an adapter disk containing electronics that process signals produced by each embedded sensor and that transmits sensor information to a data processing platform for further processing of the transmitted information.

STATEMENT AS TO FEDERALLY SPONSORED RESEARCH

[0001] This invention was made with Government support underDE-FG05-96OR22524 awarded by the U.S. Department of Energy. TheGovernment may have certain rights in the invention.

FIELD OF THE INVENTION

[0002] The invention relates to grinding wheels.

BACKGROUND

[0003] Grinding is a widely used precision machining process, accountingfor over 20% of all machining processes in the manufacturing industry.Referring to FIG. 1, one type of grinding process employs a rapidlyspinning grinding wheel 10 bonded with abrasive materials 12 (e.g.,diamond abrasive particles in a resin, vitreous, or metallic bond). Thewheel 10 grinds workpiece 14 moving slowly underneath the wheel 10.

[0004] Ceramic materials such as silicon nitride, silicon carbide,aluminum oxide, and zirconia are hard, low density materials with highwear resistance and the ability to withstand high temperatures. Grindingis often used to machine ceramic workpieces and workpieces made of othermaterials into their final shape. Costs associated with grinding includethe cost of preparing a wheel (e.g., wheel truing and dressing).

[0005] Truing typically rounds a wheel by machining excess abrasivematerial off its periphery as the wheel rotates. Initially, a truingtool engages the rotating out-of-round wheel intermittently, removingmaterial from protruding areas and progressively engaging more of theperiphery as the wheel is rounded.

[0006] Dressing conditions the wheel surface topography to achieve adesirable grinding behavior. Typically, a bonded abrasive dressing stickis passed over the wheel periphery to expose the abrasive grains byeroding away binder and possibly removing and/or fracturing diamondgrains. Re-dressing is periodically needed during grinding torecondition or resharpen a worn wheel surface. Severe and/or frequentdressing can result in excessive wheel consumption, whereas too gentleor insufficient dressing can result in a dull wheel. Dressing frequentlycan be time consuming and reduce the life of expensive abrasivematerials. On the other hand, grinding with a dull wheel causesincreased grinding forces which can lead to chatter vibration and damageto the workpiece.

[0007] For precision grinding operations, the wheel depth of cut may becomparable to or smaller than the wheel out-of-roundness. Therefore,wheel engagement with the workpiece can vary considerably during asingle rotation. The wheel may even completely lose contact with theworkpiece during part of each rotation. This unsteady behavior can havea deleterious effect on the wheel surface and the quality of the groundworkpiece.

[0008] Material removal during grinding occurs when abrasive grainsinteract with the workpiece. This interaction generally involves bothductile flow and brittle fracture. As an abrasive grain engages theworkpiece, initial cutting by ductile flow is followed by localizedfracture if the grain depth of cut and the resulting force on the grainbecomes sufficiently large. By analogy with indentation fracturemechanics, two principal types of cracks have been identified: lateralcracks which cause material removal and radial cracks which causestrength degradation. The implication of this observation is thatstrength degradation may be minimized by promoting ductile flow insteadof fracture at the ground surface. For finish grinding operations, thiswould usually require extremely slow removal rates in order to achieve asmall enough grain depth of cut and small enough force per grain.However, as a wheel is used and the abrasive material becomes duller,force levels increase, making it necessary to periodically re-dress thewheel. Periodic truing may also be necessary to restore the macroscopicshape of the wheel.

[0009] Typically, operators monitor the grinding and preparationprocesses to determine when the wheel is rounded and when the wheelneeds to be dressed. Because of the practical difficulty in assessingthe condition of a rapidly rotating wheel, operators typically managewheel usage based on observation and experience. For example, anoperator may periodically stop a grinding process to examine wheelcharacteristics (e.g., roundness and dullness) at intervals determinedby the type of workpiece being ground.

SUMMARY OF THE INVENTION

[0010] Embedded force and acoustic emission sensors and on-wheelelectronics enable an operator to continuously monitor wheel conditionsusing sophisticated real-time techniques without interrupting thegrinding process. Processing electronics can be attached to the wheelusing a modular adapter disk that enables operators to easily reuse,maintain, and modify the electronics.

[0011] In general, in one aspect, the invention features a grindingwheel system that includes a grinding wheel with at least one embeddedsensor and an adapter disk containing electronics that processes signalsproduced by each embedded sensor. The adapter disk is constructed toattach to the grinding wheel and to connect to each sensor lead whenattached. The electronics include a transmitter that transmits sensorinformation to a data processing platform. The data processing platformincludes a processor, a receiver that receives sensor informationtransmitted by the electronics, and instructions that cause theprocessor to process the received sensor information.

[0012] Different embodiments can include one or more of the followingfeatures. The grinding wheel may include at least one force sensor whichmay be positioned near the grinding wheel periphery. The grinding wheelmay include at least one acoustic emission sensor which may bepositioned near the grinding wheel rim. The sensors may be piezoceramicsensors.

[0013] The electronics can include an analog to digital converterconnected to a sensor and a digital signal processor fed by the analogto digital converter. The electronics can include a multiplexerconnected to the embedded sensors.

[0014] The data processing platform instructions can compare sensorinformation collected from different sensors at substantially the sametime and/or compare sensor information collected from a single sensor atdifferent times. The instructions can cause the processor to processsensor information using at least one neuro-fuzzy network.

[0015] In another aspect, a grinding wheel system includes a grindingwheel with at least one piezoceramic sensor embedded near the wheelperiphery for detecting wheel forces and at least three piezoceramicsensors positioned near the grinding wheel rim. An adapter diskcontaining electronics that processes signals produced by the sensorsattaches to the grinding wheel and connects to each sensor lead. Theelectronics include a multiplexer fed by the sensor leads, an analog todigital converter fed by the multiplexer, a digital signal processor fedby the analog to digital converter, and a radio frequency transmitterfed by the digital signal processor. The data processing platformincludes a processor, a radio frequency receiver that receives sensorinformation transmitted by the adapter disk electronics, andinstructions that cause the processor to process the received sensorinformation.

[0016] In another aspect, an adapter disk that processes signalsproduced by at least one sensor embedded in a grinding wheel includes atleast one lead for connecting to each embedded sensor and electronicsfor processing sensor signals.

[0017] In another aspect, a computer program, disposed on a computerreadable medium, that analyzes data acquired via sensors embedded in agrinding wheel includes instructions that cause a processor to receivesensor data representing force sensed by each sensor and analyzing thereceived data.

[0018] The computer program may determine, for example, wheel dullness,grinding mode, roundness, and/or roughness. The computer program canimplement at least one neuro-fuzzy network.

[0019] The invention provides several advantages. The grinding wheelsystem permits sophisticated real-time analysis of grinding wheelconditions. The positioning of the force and acoustic emission sensorsprevents the sensors from producing responses to normal wheel events(e.g., vibrations routinely produced during grinding). By housingelectronics in an adapter disk, operators can easily reuse, maintain,and modify the electronics. The system's data processing capabilitiesprovide a wide variety of information regarding wheel characteristics.

[0020] Unless otherwise defined, all technical and scientific terms usedherein have the same meaning as commonly understood by one of ordinaryskill in the art to which this invention belongs. Although methods andmaterials similar or equivalent to those described herein can be used inthe practice or testing of the present invention, suitable methods andmaterials are described below. All publications, patent applications,patents, and other references mentioned herein are incorporated byreference in their entirety. In case of conflict, the presentspecification, including definitions, will control. In addition, thematerials, methods, and examples are illustrative only and not intendedto be limiting.

[0021] Other features and advantages of the invention will be apparentfrom the following detailed description, and from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

[0022]FIG. 1 is a diagram of a grinding wheel.

[0023]FIG. 2 is a diagram of a grinding wheel system.

[0024]FIG. 3 is a diagram of sensor placement on a grinding wheel.

[0025]FIG. 4 is a diagram of a sensor.

[0026]FIG. 5 is a diagram of a force sensor.

[0027]FIG. 6 is a graph of force sensor response.

[0028] FIGS. 7A-7D are diagrams of vibrational patterns routinelyexperienced by a wheel.

[0029]FIG. 8 is a diagram of an adapter disk and a dummy disk attachedto a wheel.

[0030]FIG. 9 is a diagram of adapter disk electronics.

[0031]FIG. 10 is a diagram of printed circuit board layers used toprovide the adapter disk electronics.

[0032]FIG. 11 is a flow-chart of processing performed by the adapterdisk electronics and a data processing platform.

[0033]FIG. 12 is a flow-chart of a sensor calibration process.

[0034]FIG. 13 is a flow-chart of adapter disk electronics dataprocessing.

[0035]FIG. 14 is a flow-chart of a process for determining a normalforce based on a sensor response.

[0036]FIG. 15 is a diagram of a data processing platform.

[0037]FIG. 16 is a flowchart of data processing performed by the dataprocessing platform.

[0038]FIG. 17 is a flowchart of a process for determining wheelroundness.

[0039]FIG. 18 is a flowchart of a process for determining wheel surfaceroughness.

[0040]FIG. 19 is a flowchart of a process for determining wheeldullness.

[0041]FIG. 20 is a flowchart of a process for determining a wheelgrinding mode.

[0042]FIG. 21 is a flowchart of a process for determining wheel chatter.

[0043]FIG. 22 is a diagram illustrating tangential forces that act on awheel.

[0044]FIG. 23 is a flowchart of a process for determining tangentialwheel forces.

[0045]FIG. 24 is a diagram of an multiple adaptive neuro-fuzzy inferencesystem (MANFIS).

[0046]FIG. 25 is a diagram of an adaptive neuro-fuzzy inference system(ANFIS).

[0047] FIGS. 26A-25C are screenshots of a graphical user interface usedto display wheel characteristics.

DETAILED DESCRIPTION

[0048] Referring to FIG. 2, a grinding wheel system 16 includes agrinding wheel core 18 (e.g., a reusable aluminum core) coated by anabrasive material 12. The wheel core 18 includes embedded sensors (seee.g., FIG. 3) such as force and/or acoustic emission (AE) sensors. Aremovable adapter disk 24 attached to the wheel core 18 houseselectronics that process sensor signals and transmit (e.g., via wirelesstransmission) the processed signals to the data processing platform 25for analysis. A removable dummy disk 26 balances the weight of adapterdisk 24. As shown, shaft 32 supported by fork 30 rotates grinding wheel18. Rotation of wheel 18 may be electronically controlled by adapterdisk 24 or data processing platform 25. Other systems of shafts andforks can be used.

[0049] Aspects of this system are described in S. Pathare, R. Gao, B.Varghese, C. Guo, and S. Malkin, “A DSP-Based Telemetric DataAcquisition System for In-Process Monitoring of Grinding Operation,”I.E.E.E. Instrumentation and Measurement Technology Conference, May1998; S. Malkin, R. Gao, C. Guo, B. Varghese, and S. Pathare,“Development of an Intelligent Grinding Wheel for In-Process Monitoringof Ceramic Grinding”, Semi-Annual Report #1, May 1997, available on-lineat http://www.doe.gov/bridge.

[0050] Sensor Construction and Placement

[0051] Referring to FIG. 3, the wheel core 18 includes sensors such asforce detection sensors 20 a-20 k (force sensors) and acoustic emission(AE) sensors 22 a-22 d. As shown, the core 18 includes eleven forcesensors 20 a-20 k and four AE sensors 22 a-22 d symmetrically positionedabout the core 18. As shown, the wheel core 18 also includes bolt 44a-44 k and dowel pin 46 a-46 b openings to permit the adapter disk 24and the dummy disk 26 to sandwich the wheel core 18.

[0052] A core 18 may have different numbers of force and AE sensors thanthe number shown. Additionally, the sensors need not have a symmetricalconfiguration, although a symmetrical configuration offers certainadvantages discussed below. The use of both force 20 a-20 k and AEsensors 22 a-22 d permit data processing platform 25 to monitor a widevariety of wheel characteristics.

[0053] Referring to FIG. 4, glue can be used to hold each sensor (e.g.,force sensor 20) in a pre-machined slot in the core 18. A sensor 20terminal connects to metal foil 32 which may be mounted flush againstthe core 18 surface. An insulating seal 34 provides a conductive strip36 that electrically transmits a charge developed on sensor 20 inresponse to forces or acoustic emissions to adapter disk 24 electronics.A wide variety of other methods of embedding or affixing sensors can beused. Other sensors such as strain gages and/or magnetoelastic sensorscan also be used.

[0054] Although a wide variety of sensors can be used, sensors thatrespond to the piezoelectric effect (e.g., sensors having piezoceramicchips) respond to both wheel forces and acoustic emissions. Sensorresponses in the MHz range correspond to acoustic emissions. Responsesin the ten to hundred kHz range represent dynamic forces. By usingelectronic filters, a sensor's response can be easily divided into forceand acoustic emission components.

[0055] Referring to FIG. 5, a force sensor 20 produces a chargeproportional to the impulsive stress waves generated when abrasive 12grains interact with the workpiece 14. Referring also to FIG. 6, sensorresponse 20 rapidly diminishes as the sensor rotates away from the point38 where the abrasive 12 and workpiece 14 meet. That is, the amplitudeof the force signal measured depends on the angle θ formed between avertical line at the point 38 the abrasive material 12 and the workpiece14 meet and a normal line determined by the outer curvature of the core18 where the sensor 20 resides.

[0056] Referring again to FIG. 3, the wheel core 18 includes elevenforce sensors 20 a-20 k symmetrically positioned around the wheelperiphery to detect surface forces. As described below, the number andposition of the sensors can be determined based on different factors.The proximity of these peripheral force sensors 20 a-20 k to thegrinding surface increases their sensitivity to forces produced by theinteraction between the wheel 18 and workpiece 14.

[0057] The number of force sensors 20 a-20 k included in a wheel core 18depends on a variety of factors such as wheel dimensions, rotationalspeed, the configuration of the abrasive material, sensor dimensions,the complexity of data processing electronics, and space restrictions.For example, abrasive materials 12 can be glued to the wheel core 18 intwenty-two adjoining sections. The number of force sensors 20 a-20 k maybe a multiple or fraction of the sections to maintain symmetrical sensorarrangement and avoid discontinuity between sections.

[0058] The position of force sensors 20 a-20 k depends on sensitivityrequirements, sensor overload protection, and angular coverage. Forincreased sensitivity, the force sensors 20 a-20 k are sandwichedbetween the wheel core 18 and the abrasive material 12. Due to the highrigidity of the wheel core 18, the orientation of a force sensor 20 a-20k with respect to the wheel periphery does not have any measurableeffect on the sensor's 20 a-20 k angular range of coverage. To protectthe force sensors 20 a-20 k, a two-component epoxy (e.g., AralditeAV1258 with hardener HV1258) can be used to attach the abrasive material12 to the core 34.

[0059] As shown in FIG. 3, the wheel core 18 includes AE sensors 22 a-22d positioned near the wheel inner rim 40. Acoustic emission sensors 22a-22 d can be used to triangulate acoustic emissions produced bystructural imperfections (e.g., microscopic cracks) in a wheel core 18.Triangulation requires a minimum of three AE sensors, e.g., 22 a-22 c,to pinpoint a source of an acoustic emission. As shown, the core 18includes a fourth AE sensor 22 d for redundancy and increasedmeasurement accuracy.

[0060] Referring to FIGS. 7A-7D, locating AE sensors 22 a-22 d near thewheel rim 40 minimizes noise caused by the normal vibrational behaviorof the wheel core 18. FIGS. 7A-7D, show four modes (i.e., harmonicvibration response) of a wheel core 18 in normal operation. The modesproduce acoustic pressure maxima and minima 42 a-42 d near the center ofthe wheel core 18 annular region. These shapes 42 a-42 d represent areaswhere AE sensors 22 a-22 d function poorly. Thus, AE sensors 22 a-22 dare located near the wheel rim 40 as shown in FIG. 3.

[0061] Wheel Electronics

[0062] Referring to FIG. 8, a removable adapter disk 24 and removabledummy disk 26 fit around the wheel core's inner rim 40. Bolts (e.g.,bolt 44) and dowel pins 46 a-46 b secure adapter disk 24 and dummy disk26 to the wheel core 18. The adapter disk 24 holds electronics (e.g.,transmitter, power supply, and a Digital Signal Processor (DSP)) thatprocess sensor 20 a-20 k, 22 a-22 d information in a disk cavity 48. Thedummy disk 26 offers an identical mass distribution as the adapter disk24 to maintain wheel symmetry and balance. The adapter disk 24 enablessensor signal processing to occur at the wheel core 18 with minimalstructural modification of the wheel core 18. The adapter disk 24 alsofacilitates easy access and maintenance of the electronics. That is, anoperator can modify and/or update the electronics to measure otherwheel-related parameters without dismounting the wheel 18. Additionally,during maintenance or modification of the electronics, an operator cancontinue to use the wheel core 18 for conventional grinding. The modulardesign also offers operators the flexibility of using the samemeasurement electronics for a variety of wheels using differentabrasives or having different thickness and/or widths.

[0063] Referring to FIG. 9, electronics 50 process signals (e.g.electrical charges) produced by the force 20 a-20 n and AE sensors 22a-22 n. The electronics 50 can be embedded in the wheel core 18 orhoused in adapter disk 24. As shown, the electronics 50 include ananalog multiplexer 56 that selects between different sensors 20 a-20 k,22 a-22 d, a charge amplifier 58 that transforms a sensor charge into avoltage, an anti-aliasing filter 60, an analog-to-digital (A/D)converter 62, a DSP 64 that performs filtering and other data processingtasks, and a transmitter/receiver 62. Other implementations usedifferent architectures. For example, a very basic implementation doesnot use a DSP 64 at all, but instead directly transmits the analogsignal of each sensor 20 a-20 k, 22 a-22 d to the data processingplatform 25. Such a system can place a heavy burden on the dataprocessing platform 25 by transmitting such a large volume ofinformation. The use of a DSP 64, as shown, permits real-time signalprocessing at the wheel in addition to selective transmission ofgathered information.

[0064] The electronics' 50 architecture shown offers an efficient systempowered by a compact, lightweight J size 6-V battery 52. Diodeprotective circuitry 54 a-54 f connected to the input of eachmultiplexer 56 prevent damage due to high voltages from the piezoceramicsensors. The diodes 54 a-54 f offer high speeds and low reverse leakagecurrents. In addition, their low parasitic capacitance helps preservesignal quality.

[0065] Sensor input signals feed an analog multiplexer 56 (e.g., anADG608). Channel selection is achieved by using a data latch configuredas an output port of the DSP 64. The multiplexer 56 shown requires asupply current of 0.1 uA with a channel switching time of 100 ns.

[0066] Multiplexing the sensor signals makes it possible to use a singlecharge amplifier 58, anti-aliasing filter 60, and A/D converter 62 toprocess the force 20 a-20 n and AE sensors 22 a-22 n. The use of asingle set of electronic components minimizes the influence of componentvariations (e.g., amplifier gain) on signals.

[0067] Charge amplifier 58 converts a sensor's electrical charge to avoltage signal proportional to either the amplitude of the appliedforces or the acoustic emission. A high-speed operational amplifier(e.g., an AD-822) is configured as a charge amplifier 58. The lowercut-off frequency (f_(L)) of the charge amplifier 58 is set to 25 Hz byproper choice of the feed-back resistor (R1) and capacitor (C1), asgiven by:

f _(L)=1/(2πR ₁ C ₁)  [1]

[0068] Considering a time constant of the charge amplifier that is tentimes as long, the lowest wheel rotational speed required fordistortion-free force measurement is approximately 50 revolutions perminute (RPM). This number is much lower than that typically required forwheel preparation and/or grinding. Therefore, the charge amplifier 58can accurately measure force and AE signals at the low frequency end.

[0069] The charge amplifier 58 also needs to respond fast enough tocapture sensor signals. For this purpose, the highest frequencycomponent of force signals is calculated by considering that as thepoint of contact 38 sweeps past a force sensor, a force impulse (T) isgenerated whose duration is related to the peripheral wheel velocityv_(s) by:

T=w/v _(s)  [2]

[0070] where w is the width of the sensor and v_(s) is the velocity ofthe wheel perimeter. Thus, a wheel velocity of 60 m/s and sensor widthof 3 mm, T=50 us. This corresponds to a signal frequency of about 20kHz. Because AE signals are typically an order of magnitude higher, thehighest signal frequency that needs to be processed by the chargeamplifier is expected to be 500 kHz. The AD-822's bandwidth of 1.8 MHzcan easily handle this range of frequencies. For input signalattenuation, the charge amplifier 58 is preceded by a capacitive chargeattenuator. The transfer function of the charge attenuator-chargeamplifier block is given by: $\begin{matrix}{{V(s)} = {{Q(s)} \cdot \frac{A(s)}{\left\lbrack {{A(s)} + 1} \right\rbrack} \cdot \frac{{sR}_{1}}{\left\lbrack {{{sR}_{1}C_{1}} + 1} \right\rbrack} \cdot \frac{C_{2}}{\left\lbrack {C_{2} + C_{3}} \right\rbrack}}} & (3)\end{matrix}$

[0071] The charge, amplifier 58 is followed by a four-pole anti-aliasingfilter 60. The anti-aliasing filter 60 is designed using ahigh-precision, high band-width (300 MHz), current feedback amplifierAD-8011 60 having a cut-off frequency of 1 MHz. Compared to voltagefeedback amplifiers, current feedback amplifiers do not suffer fromspeed limitations due to stray capacitance and internal transistorcut-off frequencies, and, hence, are inherently faster and cover alarger bandwidth.

[0072] The anti-aliasing filter 60 feeds an A/D converter 62. The A/Dconverter 62 (e.g., AD-9223) has a resolution of 12 bits and can makethree millions samples per second. The sampling rate was chosen to meetthe Nyquist criterion for sampling signals with a bandwidth of 1 MHz.The A/D converter 62 has an on-chip voltage reference and separate powersupply pins for the analog and digital sections. The analog and digitalpower supplies are decoupled using high value capacitors mounted nearthe supply input pins (not shown) A tri-state buffer and latch bufferthe digitized output of the A/D converter 62. A separate clock chipclocks the A/D converter 62 and communicates with the DSP 64 ininterrupt mode. A flat ribbon connector (FRC) connects the output of theA/D 62 to the DSP 64.

[0073] The DSP 64 analyzes the digitized sensor signals to remove noiseand identify force and acoustic emission information. The DSP 64analyzes the spectral characteristics of the signals in addition totheir time domain behavior by performing wavelet analysis of thesignals. Wavelet analysis preserves both the frequency and time domaininformation of a signal and allows simultaneous extraction of high andlow frequency signals with different frequency resolutions. Aconventional FFT (Fast Fourier Transformation) may also be used toanalyze a signal.

[0074] As shown, the DSP 64 may be a TMS320C52, manufactured by TexasInstruments. The algorithms that implement wavelet analysis and othertransforms are often computationally demanding. The RISC-basedarchitecture (Reduced Instruction Set Computer) of a DSP 64 enablesefficient computation of large amount of data for the multiple sensors.The DSP 64 shown includes multiple internal data buses and DARAM (dualaccess RAM) which enables simultaneous addition and multiplicationoperations. The DSP 64 shown is a sixteen-bit, fixed-point digitalsignal processor offering a low supply voltage requirement (3 V),multiple on-chip serial ports (3 ports), high speed calculationcapability (100 MIPS), and a small package size compared to otherfloating-point DSPs. The DSP 64 also offers a large amount of on-chipRAM (32 kBytes), eliminating the need for external RAM and reducing theamount of space used,by the electronics. Other implementations may use amicrocontroller or microprocessor to perform the functions of DSP 64.

[0075] A transmitter/receiver 66 handles data transmission between theDSP 64 and the data processing platform 25. As shown, thetransmitter/receiver 66 is an RF transmitter. RF transmission may becarried out in the 900 MHz FCC license-free ISM (Industrial, Scientificand Medical) band. In one implementation, the RF transmitter 66 is asingle-chip hybrid IC that uses amplitude modulation in an on-off keyingmode and is capable of operating at 3V. The antenna of the RFtransmitter can be mounted flush on the outer surface of the adapterdisk 24.

[0076] The data can be compressed and can be transmitted in digital oranalog form. Compression can be configured to keep dominant frequencieswhile suppressing lesser ones. Digital transmission makes efficient useof the bandwidth, since the RF bandwidth for signal transmission haslittle relation with that of the base band. Additionally, errorcorrection mechanisms of digital transmission permit optimum utilizationof transmission power, making low power transmission possible. Further,digital transmission allows for easy time multiplexing to accommodateinput signals from multiple sensors. Digital transmission also makes itpossible to use multiple transmitters and receivers within the samefrequency band by means of TDMA (Time Division Multiple Access) withoutintroducing much complexity in the transmitter/receiver hardware.

[0077] The electronics 50 are fitted (of FIG. 9) into an adapter disk 24or into the wheel core 18 using a multi-layer design to reduce systemnoise and save space. As shown, in FIG. 10 a six-layered PCB board(Printed Circuit Board) 68 holds electronics 50 in a shape constructedto fit within adapter disk 24. Four layers (e.g., 68 b-68 e) are used assignal processing layers and two layers hold power supply rails for Vccand Ground (e.g., 68 a, 68 f). Separating the processing layers 68 b-68e from the power supply layers 68 a, 68 f significantly reduces thelength of connection tracks between individual layers. The two dedicatedpower supply layers 68 a, 68 f also provide a ripple-free voltage supplyto the circuitry. The design reduces cross-talk and other electronicinterference. Appendix A includes detailed schematics of one possibleimplementation. A wide variety of other techniques may be used to shieldthe electronics from interference and noise (e.g., foil shielding).

[0078] Referring to FIG. 11, sensor responses 72 are processed by wheelelectronics (e.g., electronics 50 in adapter disk 24) (step 74) beforetransmission (step 76) to the data processing platform for furtherprocessing (step 78). Although in this description computationalprocesses areas performed by the wheel electronics 50 (step 74) or bythe data processing platform 25 (step 78), other implementations can beused to distribute data processing functions differently.

[0079] For example, referring to FIG. 12, due to potential variations inconstruction, different sensors may produce different responses to thesame force. For example, a first force sensor may report a differentpeak charge in response to a 100 lb. load than a second force sensorbearing the same load. A calibration process 100 calibrates thedifferent sensors to prevent differences from distorting subsequentanalyses. This calibration process can be performed either by theelectronics 50 in adapter disk 24 or by the data processing platform 25.Calibration may include applying a known load (e.g., 100 lbs) to a wheel(step 102) and determining and storing the response of each sensor tothe load (step 104). Such calibration can be repeated using differentloads to determine a characteristic response curve. Thereafter, eachsensor signal processed can be normalized based on the storedcalibration data.

[0080] Referring to FIG. 13, as shown, the electronics 50 process 74signals (x₁(t), x₂(t), x₃(t)) from sensors 20 a-20 k and 22 a-22 d priorto transmission to the data processing platform 25 (step 76). The DSP 64first selects a channel (i.e., a sensor) to process (step 106). A signal(e.g, a charge) of the selected sensor is digitized (step 108) (e.g., bythe charge amplifier 58 and A/D converter 62) prior to DSP 64 analysis.

[0081] The DSP 64 continually determines the wheel's rotational speed(step 110). This value is needed in subsequent computations toaccurately determine the force represented by a sensor signal. Onemethod of determining wheel speed uses a low-pass filter to measure theduration between peak sensor pulses. This duration corresponds to thetime it takes a sensor to make one full rotation about the wheel.Another method analyzes a signal in the frequency domain to find themost dominant frequency which corresponds to the RPM. Both methods canbe used together to double-check RPM calculations.

[0082] As shown in FIG. 13, the wheel's rotational speed (i.e., RPM) isused to determine the signal amplitude produced by a force sensor (steps112 a, 112 b, 114) (x_(low)[n]). Referring also to FIG. 14, once the RPMis known (step 110), the signal from the force sensor of interest isrecorded over a predefined period of time (e.g., a few seconds). Thesignal is then windowed such that only the portion which occurs when thesensor passes over the contact point 38 is kept. The windowed signal isthen band-limited to 30 kHz (step 112 a) and passed through a bandpassfilter (step 112 b). The bandpass filter used for this purpose is tunedby the wheel RPM data (e.g., the filter's output is made proportional tothe measured force amplitude). Calculation errors are reduced byaveraging the force value for the number of rotations of the wheel. Themaximum measured force value is determined (step 114). The normal forcefor the each force sensor is obtained (nf[i]) and a normal force vector(nf) is formed and included in a formatted transmission message (step122) along with the measured RPM value.

[0083] The DSP 64 processes AE sensor signals using a high-pass filter(step 116) to identify the high-frequency AE components. The DSP 64 maythen use wavelet analysis, FFT, or other transforms to determine thefrequency-domain response of a sensor (step 118) (X_(high)[n]). The DSP64 compresses (e.g., zips) the sensor data (step 120) (X_(comp)) forinclusion in the formatted transmission message (step 122).

[0084] The Data Processing Platform

[0085] Referring to FIG. 15, a data processing platform 25 (e.g., astandard PC or PC-compatible computer) includes a display 130, akeyboard 132, a pointing device 134 such as a mouse, and a digitalcomputer 138. The digital computer 138 includes memory 140, a processor142, a mass storage device 144 a, and other customary components such asa memory bus and peripheral bus (not shown). The platform 25 furtherincludes a transmitter/receiver 136. The transmitter/receiver 136 may bea single-chip hybrid RF device interfaced to the serial port of theplatform 25.

[0086] Mass storage device 144 a can include operating system (e.g.,Microsoft Windows 95™) instructions 146 and data processing instructions78. Data processing instructions 78 can be transferred to memory 140 andprocessor 142 in the course of operation. The data processinginstructions 78 can cause the display 130 and input devices 132 and 134to provide a user interface such as a graphical user interface 150(FIGS. 26A-26C). Data processing instructions 78 can be stored on avariety of mass storage devices such as a floppy disk 144 b, CD-ROM 144c, or PROM (not shown).

[0087] Referring to FIG. 16, after receiving data (step 76), theinstructions 78 unformat (step 154) and decompress (step 156) (e.g.,unzip) a received message into its components (e.g., RPM, normal forcevector nf, and frequency information X_(comp)) Multi-resolution analysis(step 158) studies the signal at different frequency and timeresolutions to recognize distinct patterns in the input signal. The dataprocessing instructions 78 may use the data to monitor a variety ofgrinding phenomenon (step 160), such as roundness (step 162), wheeldullness (step 164), grinding mode (step 170), and/or chatter (step172). Instructions 160 may also produce estimations of tangential force(step 166), surface roughness (step 168), and/or other grindingparameters (step 174) such as temperature.

[0088] Many wheel characteristics can be determined by comparing theoutput of different sensors collected at substantially the same time.For example, referring to FIG. 17, instructions 162 may determine wheelroundness by collecting nearly contemporaneous force measurements fromdifferent force sensors (step 176). If not performed by the DSP 64 priorto transmission, the instructions 162 may normalize the collectedmeasurements based on sensor calibration data (step 178). In a roundwheel, each sensor should report nearly equal normalized forcemeasurements. The instructions 162 compare the different normalizedmeasurements using a configurable threshold (step 180). Based on thecomparison, the instructions 162 can determine whether the wheel isround (step 184) or misshapened (i.e., “out-of-round”) (step 182). Theinstructions 162 can also produce a value indicating a degree ofroundness (step 183) instead of simply producing a binaryround/not-round determination.

[0089] Referring to FIG. 18, instructions 168 can use a similartechnique to determine wheel surface roughness. When a wheel becomesrough, different force sensors produce different-normalized forcevalues. Again, by comparing substantially contemporaneously collectedforce values for different sensors (step 186), normalizing these values(step 188), and comparing the normalized values (step 190), theinstructions 168 can determine whether a wheel is smooth (step 192) orexhibits varying degrees of roughness (steps 193, 194).

[0090] Referring to FIG. 19, a variety of wheel characteristics can alsobe determined by comparing the measurements of a sensor or sensors atdifferent times. For example, as shown in FIG. 19, instructions 164determine whether a wheel has dulled by comparing (step 200) a sensor'sforce measurement at a first time (step 196) with a force measurement ofthe same sensor at a second time (step 198). As a wheel dulls, theforces exerted on each sensor tend to increase due to greater friction.Thus, if, over time, a sensor reports an increase in force, theinstructions 164 may determine the wheel is becoming increasingly dull(steps 203, 204).

[0091] One characteristic of a wheel is its grinding mode. For example,a wheel may be grinding a workpiece 14 in a continuous manner (e.g.,ductile grinding) and/or by displacing discrete chunks at non-periodicintervals (e.g., brittle grinding). As shown in FIG. 20, by collectingforce values produced by different sensors at different time periods(step 206) and determining the rate of change in these values (step208), the instructions 170 can determine whether a wheel is grindingworkpiece 14 in a ductile (step 210) or brittle (step 212) manner orsome combination thereof (step 211).

[0092] Referring to FIG. 21, instructions 172 may also determine thedegree of chatter a wheel experiences by comparing sensor responsescollected at different time periods. In one technique, the responses ofan AE sensor (or sensors) are collected at different time periods (step214) and the signals are analyzed in the frequency domain (step 216). Inthe frequency domain, chatter appears as a strong frequency outside thebandwidth typically produced by a non-chattering wheel. By comparing theAE signals from different time periods in the frequency domain (step216), frequencies corresponding to chattering can be detected (steps219, 220).

[0093] Referring to FIG. 22, grinding produces a tangential force upon awheel's surface 12. As shown, a sensor 20 at point a on the wheelsurface 12 experiences a tangential force 224. An angle, α, is formedfrom a normal 221 formed by the curvature of the wheel at point a and anormal 222 formed by the curvature of the wheel at point b (38). Thetangential force at point a equals (sine(α)×the force reported by sensor20 at point b).

[0094] Referring to FIG. 23, the relationship described above is onlyone method of determining the tangential force. Instructions 166 can useone of these methods to compute the tangential force experienced by aportion of the wheel surface 12. The instructions 166 may use depth ofcut 226, RPM 228, and wheel geometry 230 (e.g., diameter) information tocompute the tangential force (step 234) based on collected force sensorvalues (step 232).

[0095] Referring to FIG. 24, a Multiple Adaptive Neuro-Fuzzy InferenceSystem (MANFIS) 160 a can be employed to efficiently analyze sensordata. A MANFIS 160 a is a collection of several Adaptive Neuro-FuzzyInference System (ANFISs) software networks 238 a-238 n, each of whichis trained to recognize a particular feature (e.g., roundness, grindingmode, estimated tangential force, surface roughness, and grindingtemperature). Typically, each ANFIS 238 a-238 n will have three inputs,which include the normal force X, acoustic emission information Y, andthe grinding conditions Z (e.g., previously determined information).

[0096] Referring to FIG. 25, an ANFIS 238 includes a network ofdifferent communicating software layers 240-248. In a first layer 240,each input is spanned by a set of membership functions 250 a-250 f. Aset of weights in layers 242 and 244 and node functions in layer 246link the membership functions 250 a-250 f to an output layer 248. Aparticularly suitable membership function for the ANFIS architecture isthe generalized bell membership function described by three parameters:$\begin{matrix}{{\mu \quad {Ai}} = \frac{1}{1 + {\frac{x - c}{a}}^{2b}}} & \lbrack 4\rbrack\end{matrix}$

[0097] where μAi is the membership function value computed for an inputvalue x, for particular values of parameters a, b and c (called premiseparameters). The input (e.g., force x) is spanned by a set of thesemembership functions. For example, as shown, a set of two membershipfunctions 250 a-250 b span the force input. Thus, layer 240 has twooutputs for force which are fed further into the network. Similar layer240 outputs are obtained for other inputs.

[0098] Layer 242 sums the outputs from layer 240 and multiplies the sumsby weights w_(i). Layer 244 sums the outputs of layer 242 and multipliesthese outputs by normalized weights w_(i) such that: $\begin{matrix}{{\overset{\_}{W}}_{i} = \frac{W_{i}}{\Sigma \quad W_{i}}} & \lbrack 5\rbrack\end{matrix}$

[0099] In layer 246 outputs from layer 244 are combined using linearmodels 264 a-264 b. The output for each node 264 a-264 b in layer 246can be described as:

f _(i) =p _(i) X+q _(i) Y+r _(i) Z+s _(i)  [6]

[0100] where f_(i) is the node output for particular values ofparameters p_(i), q_(i), r_(i) and s_(i). These parameters are calledconsequent parameters and are determined by training as described below.Finally, ANFIS 238 output is obtained as a combination of each outputas:

f=w ₁ f ₁ +w ₂ f ₂ +w ₃ f ₃  [7]

[0101] Thus, if normal force vector (X), high frequency content (Y) andmachining condition (Z) are given, the above network can produce anoutput for specified values of weights, premise and consequentparameters.

[0102] The procedure of finding the optimized parameters and weights iscalled ANFIS 238 training. This training involves determining a numberof membership functions, values for weights, premise and consequentparameters such that the network can predict the outputs accurately. Inother words, training enables the ANFIS 238 to recognize certainpatterns in the input signal and accordingly predicts the mostappropriate output.

[0103] Training can be performed by presenting the network 238 with aset of inputs having known outputs. The parameters and weights can thenbe adjusted so that output predicted by the ANFIS 238 matches the knownoutput values. The set of known input-output values used to train theANFIS 238 is called the training data set. The training data set can beformed from data collected by the grinding wheel system 16 in parallelwith a calibrated, wired data acquisition system on the grindingmachine. The data collected by the grinding wheel system 16 forms theinput set for training, while the data collected from the calibrated,wired system forms the known output. The calibrated, wired systemincludes a force dynamometer to determine normal and tangential forces,a power transducer and thermocouples, together with measurements ofgeometric wheel form (wheel roundness, waviness etc.), and wheel surfacetopology. The training data can be used to train each individual ANFIS238 of the inference system 236. The optimized values of both thepremise and consequent parameters obtained after training the MANFIS 236in this manner is used for real-time monitoring of wheel preparation andthe grinding process.

[0104] The instructions 160 may be used to implement a MANFIS 236 whichcollects different inference systems 238 a-238 n trained to recognizedifferent wheel characteristics. The system 236 combines the power ofneural networks capable of recognizing patterns with fuzzy logic whichfacilitates easy description of inputs and outputs. The system 236 canbe trained both on-line and off-line. On-line training enables thesystem to recognize a new grinding phenomenon in any “new” environment(e.g, a new workpiece material, a new grinding wheel core, or a newgrinding wheel abrasive). Further, the individual inference systems 238a-238 n may share information with each other making them co-activeadaptive inference systems.

[0105] Referring to FIGS. 26A-26C, a graphical user interface 150 a-150c provides operators with graphic representations of grinding wheelcharacteristics. The interface 150 a-150 c screens shown are merelyexemplary. As shown in FIG. 23A, the interface 150 a may display wheelspecifications 284 (e.g., the type of abrasive material, wheel diameter,and width) and grinding conditions 282 (e.g., the workpiece material).The interface 150 a may also display other wheel characteristics such aswheel speed 270, dullness 272, roundness 274, and the grinding mode 278.The interface 150 a also permits an operator to specify a file 280 tostore data collected during a grinding session for further analysis.

[0106] Referring to FIG. 26B, the interface 150 b may also display theforce 288 or acoustic emission 286 measurements made by different wheelsensors. Referring to FIG. 26C, the interface 150 c may also indicatewheel characteristics such as tangential force 294, temperature 296,spindle power 292, and surface roughness 290.

[0107] Implementation

[0108] The invention can be implemented in hardware or software, or acombination of both. The programs should be designed to execute onprogrammable computers each comprising a processor, a data storagesystem (including memory and/or storage elements), at least one inputdevice, and at least one output device, such as a CRT or printer.Program code is applied to input data to perform the functions describedherein and generate output information. The output information isapplied to one or more output devices such as a CRT, as describedherein.

[0109] Each program is preferably implemented in a high level proceduralor object oriented programming language to communicate with a computersystem. However, the programs can be implemented in assembly or machinelanguage, if desired. In any case, the language can be a compiled orinterpreted language.

[0110] Each such computer program is preferably stored on a storagemedium or device (e.g., ROM or magnetic diskette) readable by a generalor special purpose programmable computer, for configuring and operatingthe computer when the storage media or device is read by the computer toperform the procedures described herein. The system can also beconsidered to be implemented as a computer-readable storage medium,configured with a computer program, where the storage medium soconfigured causes a computer to operate in a specific and predefinedmanner to perform the functions described herein.

[0111] Other Embodiments

[0112] It is to be understood that while the invention has beendescribed in conjunction with the detailed description thereof, theforegoing description is intended to illustrate and not limit the scopeof the invention, which is defined by the scope of the appended claims.Other aspects, advantages, and modifications are within the scope of thefollowing claims.

What is claimed is:
 1. A grinding wheel system, comprising: a grindingwheel including at least one embedded sensor, each sensor having a lead;an adapter disk containing electronics that process signals produced byeach embedded sensor, the adapter disk constructed to attach to thegrinding wheel and connect to each sensor lead, the electronicsincluding a transmitter that transmits sensor information; and a dataprocessing platform comprising: a processor; a receiver that receivessensor information transmitted by the adapter disk electronics; andinstructions that cause the processor to process the received sensorinformation.
 2. The system of claim 1, wherein the grinding wheelincludes at least one force sensor.
 3. The system of claim 2, wherein atleast one force sensor is positioned near the grinding wheel periphery.4. The system of claim 1, wherein the grinding system includes at leastone acoustic emission sensor.
 5. The system of claim 4, wherein at leastone acoustic emission is positioned near the grinding wheel rim.
 6. Thesystem of claim 1, wherein at least one sensor is a piezoceramic sensor.7. The system of claim 1, wherein the electronics comprise: an analog todigital converter connected to a sensor; and a digital signal processorfed by the analog to digital converter.
 8. The system of claim 1,wherein the electronics comprise a multiplexer connected to the embeddedsensors.
 9. The system of claim 1, wherein the instructions cause theprocessor to compare sensor information collected from different sensorsat substantially the same time.
 10. The system of claim 1, wherein theinstructions cause the processor to compare sensor information collectedfrom a sensor at different times.
 11. The system of claim 1, wherein theinstructions cause the processor to process sensor information using atleast one neuro-fuzzy network.
 12. A grinding wheel system, comprising:a grinding wheel including at least one piezoceramic sensor embeddednear the wheel periphery that detects wheel forces and at least threepiezoceramic sensors positioned near the grinding wheel rim that detectacoustic emissions, each sensor having a lead; an adapter diskcontaining electronics that process signals produced by the sensors, theadapter disk constructed to attach to the grinding wheel and connect toeach sensor lead, the electronics comprising: a multiplexer fed by thesensor leads; an analog to digital converter fed by the multiplexer; adigital signal processor fed by the analog to digital converter; and aradio frequency transmitter fed by the digital signal processor thattransmits sensor information; and a data processing platform comprising:a processor; a radio frequency receiver that receives sensor informationtransmitted by the adapter disk electronics; and instructions that causethe processor to process the received sensor information.
 13. An adapterdisk that processes signals produced by at least one sensor embedded ina grinding wheel, the adapter disk comprising a disk configured forattachment to the grinding wheel, the disk including: at least one leadthat connects to each embedded sensor; and electronics that processsensor signals.
 14. The apparatus of claim 13, wherein the electronicscomprise a wireless transmitter.
 15. The apparatus of claim 13, whereinthe electronics comprise: a multiplexer fed by each sensor lead; ananalog to digital converter connected to the multiplexer; and a digitalsignal processor connected to the analog to digital converter.
 16. Acomputer program, disposed on a computer readable medium, that analyzesdata acquired via sensors embedded in a grinding wheel, the computerprogram comprising instructions that cause a processor to: receivesensor data representing force sensed by each sensor; and analyze thereceived data.
 17. The computer program of claim 16, wherein theinstructions cause the processor to analyze the received data bycomparing sensor data collected from at least one sensor at differenttime periods.
 18. The computer program of claim 17, wherein theinstructions determine the dullness of a grinding wheel.
 19. Thecomputer program of claim 17, wherein the instructions determine thegrinding mode of a grinding wheel.
 20. The computer program of claim 16,wherein the instructions that cause the processor to analyze thereceived data compare sensor data collected from different sensors atsubstantially the same time.
 21. The computer program of claim 20,wherein the instructions determine grinding wheel roundness.
 22. Thecomputer program of claim 20, wherein the instructions determinegrinding wheel roughness.
 23. The computer program of claim 20, whereinthe instructions that analyze the data use at least one neuro-fuzzynetwork.